SYNTHESIS OF AN ADAPTIVE FUZZY CONTROL SYSTEM FOR THE WARPING PROCESS

The article discusses the synthesis of a fuzzy control system for the warping process. It considers the synthesis of an adaptive fuzzy control system designed to stabilize the yarn tension during the warping process. A mathematical model has been developed in the state-space form, explicitly defining the vectors of state variables, control inputs, and disturbances. The parameters for fuzzy rule inference are determined for various values of the process model’s time constant. A Sugeno-type fuzzy inference system is proposed to compensate for the parametric uncertainties of the control object. The Gaussian curve was chosen as the membership function since analysis shows that it provides a more accurate representation of the input signals. A comparative analysis of the efficiency of fuzzy and LQR controllers was carried out under varying dynamic characteristics of the object. A software package for the automated synthesis of fuzzy controllers has been developed, featuring the capability to analyze the system’s response surfaces. It should be noted that the program interface not only allows for the synthesis of such controllers but also enables the export of the fuzzy control system to Simulink for control quality analysis.